1. Field of the Invention
The present invention relates generally to an apparatus and method for transmitting data using multiple antennas in a wireless communication system, and in particular, to an apparatus and method for precoding transmission data in transmitting data using Multiple Input Multiple Output (MIMO).
2. Description of the Related Art
Wireless communication systems have been developed to offer users mobility that allows users to travel freely. A typical example of such wireless communication systems may include a mobile communication system. The mobile communication system converts voice signals into electrical signals, processes them and carries them on a Radio Frequency (RF) thereby providing voice services to users.
With the rapid progress of the communication technology, the mobile communication system is evolving into a high-speed, high-quality wireless packet data communication system providing data services and multimedia services beyond the earlier voice-oriented services. Recently, various mobile communication standards, such as High Speed Downlink Packet Access (HSDPA) and High Speed Uplink Packet Access (HSUPA), both defined by 3rd Generation Partnership Project (3GPP), High Rate Packet Data (HRPD) defined by 3rd Generation Partnership Project-2 (3GPP2), and 802.16 defined by Institute of Electrical and Electronics Engineers (IEEE), have been developed to support the high-speed, high-quality wireless packet data transmission services.
The present 3rd generation wireless packet data communication systems, such as HSDPA, HSUPA and HRPD, use such technologies as an Adaptive Modulation and Coding (AMC) method and a channel-sensitive scheduling method to improve transmission efficiency. With application of the AMC method, a transmitter can adjust the amount of transmission data according to the channel state. That is, in a poor channel state, the transmitter reduces the amount of transmission data to match a reception error probability to a desired level, and in a good channel state, the transmitter increases the amount of transmission data to efficiently transmit a large amount of information while matching the reception error probability to the desired level. With application of the channel-sensitive scheduling-based resource management method, the transmitter, since it selectively services a user with a good channel state among several users, increases system capacity when compared to a method of allocating a channel to a single user and servicing the user using the allocated channel. Such capacity increase is called multi-user diversity gain. In sum, the AMC method and the channel-sensitive scheduling method are methods for applying proper modulation and coding techniques at the most efficient time determined by partial channel state information fed back from a receiver.
To implement the AMC method and the channel-sensitive scheduling method, the receiver should feed back its channel state information to the transmitter. The channel state information fed back by the receiver is called a Channel Quality Indicator (CQI).
Recently, intensive research is being conducted to replace Code Division Multiple Access (CDMA), the multiple access scheme used in the 2nd generation and 3rd generation mobile communication systems, with Orthogonal Frequency Division Multiple Access (OFDMA) for the next generation mobile communication systems. 3GPP and 3GPP2 have started standardizing work on an evolved system using OFDMA. It is known that OFDMA will increase system capacity. In OFDMA, one of several causes of the capacity increase is its capability of performing scheduling in the frequency domain (Frequency Domain Scheduling). Having obtained capacity gain in the communication system using the time-varying channel characteristic through the channel-sensitive scheduling method, OFDMA is expected to obtain higher capacity gain with application of the frequency-varying channel characteristic. However, in order to support frequency-domain scheduling, the transmitter should have channel state information for each frequency. That is, there is a need for CQI feedback for each frequency, causing an increase in a load of CQI feedback.
In the next generation system, active research is being conducted on a MIMO technology based on multiple transmit/receive antennas. The term “MIMO” as used herein refers to a technology for simultaneously transmitting multiple data streams over the same resources using multiple transmit/receive antennas. In the good channel state, transmitting multiple low-modulation order data streams can increase the throughput at the same error probability, compared to increasing the modulation order. In the MIMO terminology, the dimension over which an individual data stream is transmitted is called a layer. As for the layer, a method of separately applying AMC according to the channel state is efficient in increasing system capacity. For example, Per Antenna Rate Control (PARC) is a technology for transmitting a different data stream via every transmit antenna, and its layer is a transmit antenna. Multiple transmit antennas experience different channels, and the PARC technique applies AMC such that a larger amount of data can be transmitted via a transmit antenna having a good channel state and a lesser amount of data can be transmitted via a transmit antenna with a poor channel state.
As another example, in the Per Common Basis Rate Control (PCBRC), its layer is a fixed transmission beam. Therefore, the PCBRC technique transmits a larger amount of data with a transmission beam having a good channel state, and transmits a lesser amount of data with a transmission beam having a poor channel state.
When MIMO is realized using multiple antennas, a precoding method is used to adaptively form a transmission beam according to the channel state. The term “precoding” as used herein refers to an operation in which a transmitter pre-distorts a transmission signal before transmitting the signal via a transmit antenna. If precoding is realized by linear combination, a precoding process can be expressed as shown in Equation (1),x=Es  (1)where “s” is a K×1 vector and denotes a desired transmission signal, and “x” is an M×1 vector and denotes an actual transmission signal. Further, “K” denotes the number of symbols simultaneously MIMO-transmitted over the same resources, and “M” denotes the number of transmit antennas. In addition, “E” is an M×K matrix and denotes precoding. That is, Equation (1) expresses an operation in which a MIMO transmitter with M transmit antennas applies a precoding scheme E when simultaneously transmitting K signal streams.
A precoding matrix E is adaptively determined according to a transmission MIMO channel. However, when a transmitter cannot acquire information on the transmission MIMO channel, it performs precoding according to the feedback information reported by a receiver. Accordingly, a precoding codebook including a finite number of precoding matrixes E is preset between the transmitter and the receiver. The receiver selects a precoding matrix E most preferred in the current channel state from among the precoding codebook, and feeds it back to the transmitter. Therefore, the transmitter performs MIMO transmission by applying this precoding matrix E.
The transmission signal of Equation (1), received over a MIMO channel H, is expressed as shown in Equation (2),y=Hx+z=HEs+z  (2)where “y” and “z” are both an N×1 vector and denote signals and noise signals received at N receive antennas, respectively, and ‘H’ is an N×M matrix and denotes a MIMO channel. The received signals undergo a reception combining process so that a Signal-to-Interference and Noise Ratio (SINR) of a transmission signal stream for each layer is improved. A signal r that has undergone the reception combining process can be expressed as shown in Equation (3).r=Wy=WHx+Wz=WHEs+Wz  (3)In Equation (3), “W” is an N×N matrix and denotes a reception combining process, and “r” is an N×1 signal vector. Reception techniques such as interference cancellation and Maximum Likelihood (ML) reception can be further performed to normally receive the transmission signal stream of each layer.
The conventional precoding techniques can be classified into two types. First, there is a Discrete Fourier Transform (DFT)-based precoding matrix as a precoding technique designed so as to use a spatial correlation taking into account a linear array antenna whose elements are arrayed at regular intervals. Equation (4) represents a DFT-based precoding matrix E.
                    E        =                  LF          =                                    diag              (                                                ⅇ                                      j                                          ϕ                      1                                                                      ,                                  ⅇ                                      j                                          ϕ                      2                                                                      ,                …                ⁢                                                                  ,                                  ⅇ                                      j                                          ϕ                      M                                                                                  )                        ·                                                            1                                      M                                                  [                                  exp                  (                                                            ±                      j                                        ⁢                                                                  2                        ⁢                                                  π                          ⁡                                                      (                                                          m                              -                              1                                                        )                                                                          ⁢                                                  (                                                      n                            -                            1                                                    )                                                                    M                                                        )                                ]                                                              m                  =                  1                                ,                                                                  ⁢                                  …                  ⁢                                                                          ⁢                  M                                                                              n                  =                  1                                ,                                                                  ⁢                …                ⁢                                                                  ,                M                                                                        (        4        )            In Equation (4), “F” denotes a DFT matrix or an Inverse Discrete Fourier Transform (IDFT) matrix, and “L” denotes a diagonal matrix for adjusting only the phase. A DFT-based precoding matrix, which uses the characteristic that the DFT matrix F forms spatial beams, shows excellent performance in the channel having a high spatial correlation.
Next, there is a Grassmannian Line Packing (GLP) precoding matrix designed in the antenna structure where there is no spatial correlation. The GLP precoding matrix, which improves precoding gain by extending a distance between precoding matrixes, is designed on the assumption that there is no spatial correlation. Although the DFT-based precoding matrix can also be applied to the antenna structure where there is no spatial correlation, it is known that the GLP precoding method has a better performance. Meanwhile, if there is no spatial correlation, applying PARC without precoding can also increase channel capacity. In this case, it is possible to express the precoding matrix as a unit matrix.
The precoding schemes are classified into a Single CodeWord (SCW) scheme and a Multi-CodeWord (MCW) scheme according to the number of coded packets from which multiple signal streams transmitted by the MIMO technique are generated. In the SCW scheme, one codeword is transmitted through a plurality of layers regardless of the number of layers. The MCW scheme transmits one codeword over each of multiple layers. The MCW scheme is advantageous in that a receiver can obtain additional gain through interference cancellation, because the receiver can determine success/failure in decoding of each codeword through Cyclic Redundancy Check (CRC) applied to every codeword. However, the MCW scheme, as it increases the number of transmission codewords, may consume additional resources which linearly increase to apply CRC, and may increase in the complexity of the receiver. A Dual CodeWord (DCW) scheme has been designed as a proposed trade-off for obtaining the rate improvement effect of the MCW scheme while compensating its disadvantages. In the DCW scheme, a maximum of two codewords are transmitted through multiple layers regardless of the number of layers.
FIG. 1 is a diagram illustrating an example of a general SCW scheme-based MIMO (SCW MIMO) transceiver structure. With reference to FIG. 1, a description will be made of a general SCW MIMO transceiver structure.
A desired transmission data stream is input to a channel coding and modulation unit 101 where it is converted into one coded packet signal stream after undergoing a channel coding and modulation process. The signal converted into a packet signal stream is input to a demultiplexer 103 for MIMO transmission. The demultiplexer 103 demultiplexes the signal stream into K signal streams. The K signal streams demultiplexed in this way are linearly converted into M signal streams to be transmitted via associated transmit antennas by means of a precoder 105. The precoding process performed in the precoder 105 can be considered that K signal streams are processed such that they are transmitted through different transmission beams. The precoded M signal streams are transmitted via associated transmit antennas 109a through 109m by means of associated transmission processors 107a through 107m. The transmission processors 107a through 107m each includes not only the process of making CDMA or OFDMA signals but also the filtering and RF processing process performed in each antenna. The transmitted signals are received at N receive antennas 111a through 111n, and the signals received at the receive antennas 111a through 111n are restored to baseband signals by means of associated reception processors 113a through 113n. The reception-processed signals are output to a reception combiner 115 where they undergo signal combining separately for each transmit antenna. The signals combined separately for each transmit antenna are input to a multiplexer 117 where they are restored to the desired original transmission signal stream. Then the restored signal undergoes demodulation and channel decoding in a demodulation and channel decoding unit 119, restoring the desired original transmission data stream.
SCW MIMO is characterized in that since the transmitter generates multiple transmission signal streams by applying one channel coding and modulation unit 101, it only needs to receive one CQI feedback. However, the number of MIMO transmission signal streams, i.e., the number K of transmission MIMO layers, should be adjusted according to the channel state. The number K of transmission MIMO layers will be referred to herein as ‘Rank’. Therefore, a feedback of SCW MIMO is composed of one CQI representing a channel state of transmission MIMO layers and the number Rank of transmission MIMO layers.
FIG. 2 is a diagram illustrating an example of a general MCW scheme MIMO (MCW MIMO) transceiver structure. With reference to FIG. 2, a description will now be made of an example of a general MCW MIMO transceiver structure.
In MCW MIMO, unlike in SCW MIMO, different coded packet signal streams are transmitted through individual MIMO layers. Therefore, a desired transmission data stream is input to a demultiplexer 201 where it is demultiplexed into as many signal streams as Rank. The demultiplexed signal streams are converted into signal streams associated to corresponding MIMO layers by means of different channel coding and modulation units 203a through 203k. In the following transmission process, the signal streams are transmitted using the same structure as that of the SCW MIMO transmitter. That is, the signals to be transmitted via M transmit antennas are generated by means of the precoding process and the transmission process for individual transmit antennas. It should be noted that the same or similar elements are denoted by the same reference numerals throughout FIGS. 1 and 2. However, in FIG. 2, channel coding and modulation processes 203a through 203k can be implemented with one channel coding and modulation unit. In this case, FIG. 2 is similar to FIG. 1 in terms of the channel coding and modulation process.
The MCW MIMO reception process is also similar to the process performed in the SCW MIMO receiver in several steps just after reception. That is, the MCW MIMO receiver and the SCW MIMO receiver use the same reception process of converting signals received via individual antennas into baseband signals, and the reception combining process of combining the received signals into transmission signals for individual layers. Therefore, the same elements are denoted by the same reference numerals. The restored signals may include mutual interference. The MCW MIMO receiver, since the transmission signals have undergone different coding and modulation for individual layers, can cancel a first restored signal of a particular layer to prevent the signal from causing interference to another layer. With application of such an interference canceller 205, it is possible to improve channel capacity of MIMO layers. As a result, it is possible to transmit more data through MCW MIMO transmission.
Although the receiver structure shown in FIG. 2 uses the interference canceller 205 by way of example, it can use a reception method of another type. Since the interference canceller 205 is used herein, a detailed description will be given below of the reception process based on the interference canceller 205 given in FIG. 2 by way of example.
When a signal of one layer is successfully restored by means of a demodulation and channel decoding unit 203, the interference canceller 205 cancels interference using the restored signal. The interference-canceled signal stream 207 is delivered back to the demodulation and channel decoding unit 203, and the restoration and interference cancellation is repeated until signals of all layers are successfully restored or there is no more signal of layers that will undergo restoration. Finally, the restored multiple signal streams for individual layers are restored to one desired transmission data stream by means of a multiplexer 209.
The MCW MIMO transmitter is characterized in that it should receive a CQI feedback for each layer since it generates multiple transmission signal streams by applying different channel coding and modulation units 203a through 203k for individual layers. Meanwhile, Rank can be implicitly expressed by setting a predefined CQI value indicating ‘no-transmission’ among CQI values, rather than separately feeding back CQIs. Therefore, in the MCW MIMO receiver, a feedback is composed of multiple CQIs representing channel states of individual transmission MIMO layers.
As described above, the SCW and MCW MIMO techniques have their advantages and disadvantages. Therefore, there is a need for a more effective MIMO technique.